How can you measure the magnitude of an economic crisis? By the number of lost jobs, foreclosures, GDP drop, number of defaulting banks and corporations, deflation? Or by the drop in stock-market indices? All these parameters do indeed reflect the severity of a crisis. But how about a single holistic index which takes them all into account? This index is complexity and in particular its variation. Let us examine, for example, the US sub-prime crisis. The complexity of the US housing market in the period 2004-2009 is illustrated in the above plot. A total of fifty market-specific parameters have been used to perform the analysis in addition to fifteen macroeconomic indicators such as the ones mentioned above. The "bursting bubble" manifests itself via a complexity increase from a value of approximately 19 to around 32. With respect to the initial value this means an increase of 40%. The arrow in the above plot indicates this jump in complexity and this number represents a systemic measure of how profound the US housing market crisis is.
In summary, the magnitude of a crisis can be measured as follows:
M = | C_i - C_f | / C_i
where C_i is the value of complexity before the crisis and C_f the value during crisis. The intensity of a crisis can be measured as the rate of change of complexity.
Serious science starts when you begin to measure.